Triple
T20203987
| Position | Surface form | Disambiguated ID | Type / Status |
|---|---|---|---|
| Subject | D03 |
E493299
|
entity |
| Predicate | line |
P1293
|
FINISHED |
| Object | Orange Line |
—
|
NE NERFINISHED |
How this triple was built (2 steps)
Every LLM step that produced this triple, in pipeline order — named-entity classification, the disambiguation choices (the exact options shown, with the pick highlighted), and the generated description. The batch + timestamp of each is in the Provenance table below.
NER
Named-entity recognition
gpt-5-mini
Instruction
Given a phrase, classify it is english named entity (e.g., persons, organizations, works of art) in Latin script, or not (e.g., literals, dates, URLs, verbose phrases). For disambiguation, the statement where the phrase occurs as object is also given. Please return a JSON object with `phrase` (string, the phrase being analyzed) and `is_ne` (boolean, indicating whether the phrase is a Named Entity).
Input
Phrase: Orange Line | Statement: [D03, line, Orange Line]
NED1
Entity disambiguation (via context triple)
gpt-5-mini-2025-08-07
Target entity: Orange Line Context triple: [D03, line, Orange Line]
-
A.
Orange Line
The Orange Line is a major corridor of the Delhi Metro system that connects central Delhi to the Indira Gandhi International Airport and surrounding areas.
-
B.
Orange Line
The Orange Line is one of the primary rapid transit routes in the Washington Metro system, running east–west through Washington, D.C. and its Virginia and Maryland suburbs.
-
C.
Orange Line
The Orange Line is a light rail route in the Dallas Area Rapid Transit (DART) system serving key destinations including Dallas/Fort Worth International Airport and several northern suburbs.
-
D.
Orange Line
The Orange Line is a rapid transit line in the Kaohsiung Mass Rapid Transit (KMRT) system in Kaohsiung, Taiwan.
-
E.
Orange Line
The Orange Line is one of the urban cable car routes in La Paz–El Alto’s Mi Teleférico transit system, known for its orange-branded gondolas connecting key areas of the cities.
- F. None of above.
- G. Unsure - the case is ambiguous/there is not enough information to decide. chosen
Provenance (2 batches)
The batch behind each pipeline step, in order, with when it ran. Timestamps are batch-level — stages were processed in waves, so the object chain (NER → NED1 → NEDg → NED2) reads in order, but predicate / elicitation batches can sit in a different wave.
| Step | Stage | Batch ID | Status | When |
|---|---|---|---|---|
| creating | Elicitation | batch_69da6269614c8190bb40475d9d477358 |
completed | April 11, 2026, 3:02 p.m. |
| NER | Named-entity recognition | batch_69e66d8f90108190b72e37c0056de0f8 |
completed | April 20, 2026, 6:16 p.m. |
Created at: April 11, 2026, 11:38 p.m.